Detecting anomalous events to trigger the uploading of video to a video storage server

ABSTRACT

A computer-implemented method includes: storing, by a computing device, pixel-based classification rules in a memory of a computing device; storing, by the computing device, video uploading rules that identify a subset of a plurality of cameras implemented within a vehicle for which video should be uploaded in the memory of the computing device; detecting, by the computing device, satisfaction of video upload event criteria based on video or image data from at least one of the plurality of cameras and vehicle information comprising one of vehicle sensor information and vehicle diagnostic information; determining, by the computing device, a subset of the plurality of cameras based on the detecting the satisfaction of the video upload event criteria; and uploading, by the computing device, video captured by only the subset of the plurality of cameras to a video storage server.

BACKGROUND

The present invention generally relates to uploading video to a videostorage server and, more particularly, to detecting events that triggerthe uploading of video to a video storage server.

Vehicles may include a group of cameras arranged in a manner to capturefull 360-degree video of the vehicle's surroundings. Video of thevehicle's surrounds can be useful for various applications, for example,for identifying road hazards, driving habits or actions of the vehicleor surrounding vehicles, traffic light status during vehicle travel,etc.

SUMMARY

In an aspect of the invention, a computer-implemented method includes:monitoring, by a computing device, video or image data captured by aplurality of cameras implemented within a vehicle; monitoring, by thecomputing device, vehicle information associated with the vehicle,wherein the vehicle information includes sensor information reported bytire pressure sensors or impact sensors of the vehicle, or vehiclediagnostic information; detecting, by the computing device, satisfactionof particular video upload event criteria for which video should beuploaded for secure storage and future analysis, wherein the detectingthe satisfaction of the video upload criteria is based on the monitoringthe video or image data and the vehicle information; and uploading, bythe computing device, video captured by a subset of the plurality ofcameras to a video storage server, wherein the subset of the pluralityof cameras include cameras capture the video or image data used todetect the satisfaction of the video upload event criteria or areassociated with the vehicle information used to detect the satisfactionof the video upload event criteria.

In an aspect of the invention, there is a computer program product fortriggering the uploading of video from a subset of cameras of aplurality of cameras implemented in a vehicle. The computer programproduct comprises a computer readable storage medium having programinstructions embodied therewith, the program instructions executable bya computing device to cause the computing device to: monitor video orimage data captured by the plurality of cameras; detect an anomalousevent based on the monitoring of the video or image data, wherein theanomalous event relates to a collision, a road hazard, or an aggressivedriver; determine a subset of cameras of the plurality of cameras thatcaptured the video or image data associated with the anomalous event;and upload video captured by the subset of cameras of the plurality ofcameras to a video storage server.

In an aspect of the invention, a system comprises: a CPU, a computerreadable memory and a computer readable storage medium associated with acomputing device; program instructions to monitor video or image datacaptured by a plurality of cameras implemented within a vehicle; programinstructions to monitor vehicle information associated with the vehicle;program instructions to detect an anomalous event based on themonitoring of the video or image data and the monitoring of the vehicleinformation, wherein the detecting the anomalous event include detectinga satisfaction of criteria defining the anomalous event, wherein theanomalous event relates to a collision, a road hazard, or an aggressivedriver; program instructions to determine a subset of cameras of theplurality of cameras that captured the video or image data associatedwith the anomalous event, wherein a field of view of the subset ofcameras of the plurality of cameras face a direction associated with theanomalous event; and program instructions to upload video captured bythe particular cameras of the plurality of cameras within a particulartime window to a video storage server. The program instructions arestored on the computer readable storage medium for execution by the CPUvia the computer readable memory

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is described in the detailed description whichfollows, in reference to the noted plurality of drawings by way ofnon-limiting examples of exemplary embodiments of the present invention.

FIG. 1 depicts a cloud computing node according to an embodiment of thepresent invention.

FIG. 2 depicts a cloud computing environment according to an embodimentof the present invention.

FIG. 3 depicts abstraction model layers according to an embodiment ofthe present invention.

FIG. 4 shows an overview of an example implementation in accordance withaspects of the present invention

FIG. 5 shows a block diagram of example components of an event detectcomponent in accordance with aspects of the present invention.

FIG. 6 shows an example flowchart for detecting an event to triggeruploading video to a video storage server in accordance with aspects ofthe present invention.

DETAILED DESCRIPTION

The present invention generally relates to uploading video to a videostorage server and, more particularly, to detecting events that triggerthe uploading of video to a video storage server. Uploading videocaptured by vehicles (e.g., to a cloud server) may be useful to preservevideo footage and to later analyze the video for various purposes (e.g.,identifying road hazards, identifying at-fault drivers in an accident,etc.). Accordingly, vehicles may include a suite of cameras to capturevideo as the vehicle is being driven. However, uploading all videocaptured by vehicles while the vehicle is being driven can consume aninordinate amount of network resources and computer storage resources.Further, a vast majority of video may not be of interest to an end-userwho may be only interested in a few seconds of video immediately priorto and/or immediately after a particular event. For example, a user maywish to view video captured by a vehicle at a small time window aroundthe time when the vehicle experiences an anomaly (e.g., a tire puncture,an impact, engine malfunction, etc.). As another example, a user maywish to view a video at a small time window around the time when thevideo captures an anomalous event (e.g., an event of interest in whichvideo of the event should be securely stored by a remote server forfuture analysis). For example, an anomalous event for which video may beuploaded and stored may include a traffic accident, bicycle accident,etc. Accordingly, aspects of the present invention may include systemsand/or methods that detect the occurrence of a particular event (e.g.,an anomalous event) and, in turn, upload a portion of the video at aparticular time prior to the event and after the event to a cloud serverfor analysis. Further, the systems and/or methods may determine aparticular direction in which video of interest has been captured.

As an example, the systems and/or methods may detect an event, such as atire puncture (e.g., based on tire pressure sensors and a vehiclediagnostics system). Based on detecting the tire puncture, videocaptured by the vehicle's front-facing camera immediately prior to thetire puncture may be uploaded to the cloud server, since this videowould show possible debris, potholes, etc., present on the road thatwould cause a tire puncture. Additionally, or alternatively, videocaptured by the vehicle's rear-racing camera after the tire puncture maybe uploaded to the cloud server. In this way, the video may be analyzedto identify a road hazard (e.g., pot hole, debris, disabled vehicle,pulled over vehicle, etc.) that caused the tire puncture. Further, onlyvideo from them most pertinent angles from cameras that havepredominantly captured an event would be uploaded to preserve networkand storage resources.

As described herein, other events may trigger the uploading of videocaptured by a vehicle. For example, image analysis techniques may beused to detect an anomaly or risky situation based on the video capturedby vehicle cameras. As an illustrative example, image analysistechniques may be used to detect a vehicle accident (e.g., a motorvehicle accident, a bicycle accident, etc.). Video from the particularcamera(s) in the vehicle having a field of view facing the direction inwhich the anomaly was detected may then be uploaded to the cloud server.In this way, only video from cameras with fields of view facing in adirection that captured possible events of interest may be uploaded,thereby saving network and digital storage resources. Further, theuploaded video may be used to analyze incidents and conditionssurrounding an event (e.g., the incidents/conditions leading up to amotor or non-motor vehicle accident, road hazard, etc.).

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 1, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a nonremovable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 2, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 3, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 2) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 3 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and event detection 96.

Referring back to FIG. 1, program/utility 40 may include one or moreprogram modules 42 that generally carry out the functions and/ormethodologies of embodiments of the invention as described herein (e.g.,such as the functionality provided by event detection 96). Specifically,program modules 42 may monitor video and image data, monitor vehicleinformation, detect the satisfaction of particular video upload eventcriteria based on the monitoring, and upload video snippets to a videostorage server based on detecting the satisfaction of video upload eventcriteria. Other functionalities of program modules 42 are describedfurther herein such that program modules 42 are not limited to thefunctions described above. Moreover, it is noted that some of programmodules 42 can be implemented within the infrastructure shown in FIGS.1-3. For example, program modules 42 may be representative of an eventdetection component 415 FIG. 4.

FIG. 4 shows an overview of an example implementation in accordance withaspects of the present invention. As shown in FIG. 4, a vehicle 400 mayinclude a suite of cameras 405 that capture video from directions fromthe vehicle. For example, the vehicle 400 may include a front-facingcamera, a rear-facing camera, side-facing cameras, diagonal-facingcameras, etc. During vehicle operation, vehicle 400 may record videousing its cameras 405. As video is being recorded, a video analyzer 410may provide video/image data to a video upload event detection component415. The event detection component 415 may also communicate with avehicle diagnostic system 420 that may provide vehicle diagnosticinformation to event detection component 415. For example, vehiclediagnostic system 420 may provide vehicle diagnostic information, suchas tire pressure information, fluid level/temperature information,maintenance information, etc. Additionally, or alternatively, vehiclediagnostic system 420 may provide information from accident or impactsensors implemented in the vehicle 400. Based on the video/image dataand/or the vehicle diagnostic information, event detection component 415may detect the occurrence of an event in which video captured by thecameras 405 should be uploaded or provided to a video storage server425.

In embodiments, event detection component 415 may detect an anomalousevent (e.g., an unusual or high-risk event) from the video/image dataand/or the vehicle diagnostic information. For example, event detectioncomponent 415 may identify objects and/or events from the video/imagedata (received from video analyzer 410) based on a stored set of rulesthat define the types of objects/events corresponding to the video/imagedata. As an example, event detection component 415 may store pixel-basedclassification rules that may be used to identify that a particularvideo or image includes an object of a damaged motor vehicle, damagedbicycle, or the like. The event detection component 415 may determinethat a particular object or set of video/image data corresponds to ananomalous event based on the stored set of rules. In embodiments, eventdetection component 415 may further detect an anomalous event based onthe vehicle diagnostic information (e.g., low tire pressures, impact onthe vehicle, etc.).

Based on detecting the occurrence of an anomalous event, event detectioncomponent 415 may upload video from a particular time window (e.g.,“snippet”) surrounding the anomalous event (e.g., a particular amount oftime before and/or after the event). For example, event detectioncomponent 415 may upload video from a local storage device implementedwithin the vehicle to video storage server 425. Further, event detectioncomponent 415 may upload the video only from the camera(s) facing adirection in which the event can be viewed. For example, if an event wasdetected based on video/image data from the front left camera 405,snippets from the front left camera 405 may be uploaded to video storageserver 425. Alternatively, video snippets may be provided from multiplecameras 405 for certain event types.

As described herein, events may be categorized based on type (e.g.,accident event, road hazard event, etc.) For example, event detectioncomponent 415 may store rules that identify particular vehiclediagnostic data and video/image data associated with a particular eventtype. In embodiments, video may be uploaded to different video storageservers 425 associated with different parties (e.g., based on the typeof event). For example, events categorized as a road hazard (e.g., basedon vehicle diagnostic data indicating a flat tire) may be provided to avideo storage server 425 associated with an agency responsible formaintaining the road in which the hazard was present. As anotherexample, events categorized as an accident (e.g., data from impactsensors and/or video/image data identifying damaged vehicles) may beprovided to a video storage server 425 associated with a law enforcementagency, insurance company, roadside assistance company, newsorganization, traffic reporting organization, etc. Additionally, oralternatively, videos may be uploaded to a video storage server 425associated with the driver. In embodiments, videos may be stored for aparticular period of time after which time the videos may beautomatically deleted (e.g., to make storage space available foradditional incoming videos). As described herein, cameras 405, videoanalyzer 410, event detection component 415, vehicle diagnostic system420, and/or video storage server 425 shown in FIG. 4 may include one ormore of the components of computer system/server 12 of FIG. 1.

FIG. 5 shows a block diagram of example components of event detectcomponent 415 in accordance with aspects of the present invention. Asshown in FIG. 5, event detection component 415 may include a video eventrules repository 510, a vehicle information monitoring module 520, anobject detection and monitoring module 530, and a video uploading module540. In embodiments, event detection component 415 may includeadditional or fewer components than those shown in FIG. 5. Inembodiments, separate components may be integrated into a singlecomputing component or module. Additionally, or alternatively, a singlecomponent may be implemented as multiple computing components ormodules.

The video event rules repository 510 may include a data storage device(e.g., storage system 34 of FIG. 1) that stores a set of rules,definitions, or criteria defining events (e.g., anomalous events) basedon vehicle data and/or video/image data. For example, the video eventrules repository 510 may store pixel-based classification rules used toidentify objects from video/image data. Further, the video event rulesrepository 510 may store rules that associate particular video/imagecriteria (e.g., objects, patterns, motions, etc.) to a particular eventtype (e.g., an anomalous event that triggers the upload of video tovideo storage server 425). The video event rules repository 510 may alsostore rules that identify event types based on other criteria, such asvehicle data (e.g., diagnostic data, such as tire pressure, vehicleimpact data, etc.). The video event rules repository 510 may also storevideo uploading rules that identify particular cameras or a subset ofcameras on vehicle 400 for which video should be uploaded to videostorage server 425 (e.g., based on monitored data). The video eventrules repository 510 may also store video uploading rules that identifythreshold values for data reported by tire pressures or impact sensorsthat that trigger an event for which video should be uploaded. Forexample, video event rules repository 510 may store a rule to uploadvideo from a subset of cameras when a tire pressure value drops below athreshold within a relatively short period of time, thus indicating aroad hazard (e.g., a pothole or debris causing a flat tire when struck).Additionally, or alternatively, video event rules repository 510 maystore a rule to upload video from a subset of cameras when a value forimpact sensors exceeds a threshold, thus indicating a collision.Further, the video event rules repository 510 may store video uploadingrules that identify particular time windows for video to upload (e.g.,based on the type of event). In embodiments, rules stored by the videoevent rules repository 510 may be preconfigured, defined by authorities,user-configurable, and/or non-configurable.

The vehicle information monitoring module 520 may include a programmodule (e.g., program module 42 of FIG. 1) that monitors vehicleinformation (e.g., diagnostic information and/or sensor information fromvehicle diagnostic system 420). For example, the vehicle informationmonitoring module 520 may monitor values reported by impact sensors,tire pressure sensors, and/or other types of sensors.

The object detection and monitoring module 530 may include a programmodule (e.g., program module 42 of FIG. 1) that detects and monitorssurrounding objects from video captured by the cameras 405. Inembodiments, the object detection and monitoring module 530 may detectobjects based on pixel-based classification rules stored by the videoevent rules repository 510. Additionally, or alternatively, the objectdetection and monitoring module 530 may monitor motions for videocaptured by the cameras 405. In embodiments, the object detection andmonitoring module 530 may receive video analysis data from videoanalyzer 410. For example, video analyzer 410 may analyze the video datato identify objects from video and image data, and provide informationregarding the identified objects to the object detection and monitoringmodule 530. In embodiments, processes described as being performed bythe object detection and monitoring module 530 may also be performed byvideo analyzer 410.

The video uploading module 540 may include a program module (e.g.,program module 42 of FIG. 1) that detects the occurrence of an event anduploads video to video storage server 425 based on detecting theoccurrence of an event (e.g., the satisfaction of criteria for rulesstored by the video event rules repository 510). As described herein,the video uploading module 540 may detect the occurrence of an eventwhen particular criteria for a rule has been satisfied or met (e.g., forrules stored by the video event rules repository 510). For example, thevideo uploading module 540 may detect the occurrence of an event basedon detecting certain objects, object patterns, and/or motions (e.g., asmonitored and detected by the object detection and monitoring module530). Additionally, or alternatively, the video uploading module 540 maydetect the occurrence of an event based on the satisfaction of criteria(e.g., satisfaction of threshold values) related to vehicle information(e.g., diagnostic information such as tire pressure, impact informationreported by impact sensors of the vehicle, etc.). In other words, thevideo uploading module 540 may determine events and event types based onvehicle information (e.g., as monitored by the vehicle informationmonitoring module 520), objects and motion surrounding the vehicle(e.g., as detected and monitored by the object detection and monitoringmodule 530), and rules that define the criteria of the event types(e.g., as stored by the video event rules repository 510). Inembodiments, video uploading module 540 may identify a subset of camerasthat captured an anomalous event (e.g., cameras whose field of viewfaced a direction of the anomalous event).

As described herein, the video uploading module 540 may determine anevent type based on the satisfaction of particular criteria associatedwith the event type. For example, the video uploading module 540 maydetermine a “road hazard” event type based on a sudden drop in tirepressure without other impacts to other parts of the vehicle (e.g.,based on a rule that defines a road hazard as an event when there is asudden drop in tire pressure without other impacts to other parts of thevehicle). As another example, the video uploading module 540 maydetermine a “surrounding vehicle accident” event type based onimage/video data indicating that a surrounding vehicle became damaged orcollided with another object (e.g., when a surrounding vehicle's body isintact and later shows sign of damage as determined by image/videoanalysis and classification techniques). For example, the “surroundingvehicle accident” event type may be determined based on a rule thatdefines the “surrounding vehicle accident” event type as an event inwhich a surrounding vehicle becomes damaged or collides with anotherobject. As another example, the video uploading module 540 may determinea “surrounding non-motor vehicle accident” such as a bicycle accident(e.g., when image/video analysis and classification techniques detect abicycle in a parallel orientation to the road). As another example, thevideo uploading module 540 may determine a “vehicle accident” whenimpact sensors of the vehicle in which event detection component 415 isimplemented report impact measurements indicative of an accident orcollision.

Additionally, or alternatively, the video uploading module 540 maydetermine other types of events based on rules that define the eventtypes. For example, the video uploading module 540 may determine a“multicar accident” based on detecting objects, patterns, and motionsindicative of a multicar accident. As another example, the videouploading module 540 may determine an “aggressive driving” event basedon motion patterns of surrounding vehicles. As another example, thevideo uploading module 540 may determine a “disabled vehicle” or“stopped vehicle” event based on the presence of a stationary vehicle ona shoulder lane. As another example, the video uploading module 540 maydetermine a “hostile individual” event based on the an individualapproaching a driver side of the vehicle while a driver is currently inthe vehicle as identified by weight sensors implemented in the driver'sside seat, etc.

As described herein, the video uploading module 540 may upload video tovideo storage server 425 based on detecting the occurrence of an event.In embodiments, the video uploading module 540 may determine a snippetor time window for video to upload (e.g., based on the determined eventtype). For example, for certain event types, the video uploading module540 may upload video for a time window one minute prior to the event toone minute after the event. For another event type, the video uploadingmodule 540 may upload video for a shorter time window (e.g., dependingon the duration of the time window that is needed to analyze thepreceding and surrounding incidents leading up to the detected event).In embodiments, the video uploading module 540 may upload video in adirectionally intelligent manner in which only video captured by cameras405 facing a direction that relevant to the event. In embodiments, thevideo uploading module 540 may upload video from a single camera 405 ormultiple cameras 405 depending on the event type. Additionally, oralternatively, the video uploading module 540 may provide the video todifferent video storage servers 425 associated with different partiesbased on the event type. In embodiments, the video uploading module 540may upload video as a computer file and may also attach metadataregarding the video (e.g., date/time of video capture, event type,vehicle owner information, registration information, license plateinformation, make/model, vehicle location based on global positioningsystem (GPS) data received by vehicle diagnostic system 420, etc.). Inembodiments, the video uploading module 540 may provide video only,audio only, or both video and audio depending on the event type.

In embodiments, the video uploading module 540 may provide an indicationregarding the event (without providing the video itself) to a serverthat maps and maintains information identifying road events, such asroad hazards, accidents, etc. Further, the video uploading module 540may provide an indication regarding the event to law enforcement and/ormedical assistance personnel (e.g., to dispatch law enforcement torespond to an “emergency hostile individual” event when an aggressiveindividual is detected).

In embodiments, the video uploading module 540 may direct a displaywithin the vehicle (e.g., associated with vehicle diagnostic system 420)to display an indication that an event has been detected and that videois being uploaded to video storage server 425. In embodiments, the videouploading module 540 may receive a manual instruction (e.g., via aphysical button or via a user device) to upload video to video storageserver 425. For example, a user or driver may select to upload videostorage server 425 if the video uploading module 540 has not detected anevent but if the user wishes to upload video. In embodiments, the videouploading module 540 may, over a period of time, learn the conditions ofthe vehicle surroundings in which a manual instruction is received toupload video. Further, the video uploading module 540 may create a newrule identifying the conditions so that events can be automaticallydetected in the future and video can be automatically uploaded.

FIG. 6 shows an example flowchart for detecting an event to triggeruploading video to a video storage server in accordance with aspects ofthe present invention. The steps of FIG. 6 may be implemented in theenvironment of FIG. 4, for example, and are described using referencenumbers of elements depicted in FIG. 4. As noted above, the flowchartillustrates the architecture, functionality, and operation of possibleimplementations of systems, methods, and computer program productsaccording to various embodiments of the present invention.

As shown in FIG. 6, process 600 may include monitoring video and imagedata (step 610). For example, as described above with respect to theobject detection and monitoring module 530, event detection component415 may monitor video and image data captured by cameras 405 of avehicle.

Process 600 may further include monitoring vehicle information (step620). For example, as described above with respect to the vehicleinformation monitoring module 520, event detection component 415 maymonitor vehicle information gathered and received by a vehiclediagnostic system 420.

Process 600 may also include detecting the satisfaction of particularvideo upload event criteria based on the monitoring (step 630). Forexample, as described above with respect to the video uploading module540, event detection component 415 may detect the satisfaction ofparticular video upload event criteria based on the monitoring. Asdescribed above, event detection component 415 may detect thatvideo/image data and vehicle diagnostic information meet particularcriteria associated with a rule that defines an event and an event type.As described herein, different sets of criteria may define differentevents and event types, which in turn, defines time windows andparticular cameras 405 for videos to upload. As described herein, thevideo upload event criteria may define an anomalous event (e.g., anevent of interest in which video of the event should be uploaded to andsecurely stored by video storage server 425 for future analysis).

Process 600 may further include uploading a video snippet to a videostorage server based on detecting the satisfaction of the video uploadevent criteria (step 640). For example, as described above with respectto the video uploading module 540, event detection component 415 mayupload a video snippet to video storage server 425. In embodiments,event detection component 415 may determine a particular duration andtime index for the video snippet, and may provide the video to differentparties associated with different video storage servers 425 based on theevent type. Further, event detection component 415 may determineparticular cameras 405 for which video should be uploaded based on thevideo and image data that was used to detect the satisfaction of thevideo upload event. In other words, event detection component 415 mayupload video captured by the cameras 405 that captured video of ananomalous event (e.g., video having objects, motions, or patterns thatis defined as anomalous based on rules stored by the video event rulesrepository 510). For example, event detection component 415 may uploadvideo captured by the cameras 405 that faced a direction of theanomalous event.

In embodiments, video snippets from surrounding vehicles may beuploaded. For example, when a event detection component 415 associatedwith a particular vehicle detects an event, event detection component415 may communicate with event detection component 415 of other nearbyvehicles (e.g., using standard language communication via a personalarea network connection and/or other types of network connection) todirect event detection component 415 to upload videos from theirrespective vehicles' point of view. In this way, video from multiplevehicles may be uploaded for later analysis in the event only onevehicle's event detection component 415 detects an event but when videofrom other vehicle's points of view may be helpful in an analysis.

As described herein, video stored by video storage server 425 may beanalyzed to better investigate the incidents that led up to a particularevent (e.g., an accident, road hazard, aggressive driving, hostileactivity, anomalous activity, etc.). The video may be used for aforensic analysis to investigate the event. Also, as discussed above,snippets of video are uploaded rather than all video captured by thecameras 405 to reduce storage and network resources. For example, videofrom the most pertinent angles may be provided such that full coverageof incidents leading up to an event may be stored by video storageserver 425.

In embodiments, a service provider, such as a Solution Integrator, couldoffer to perform the processes described herein. In this case, theservice provider can create, maintain, deploy, support, etc., thecomputer infrastructure that performs the process steps of the inventionfor one or more customers. These customers may be, for example, anybusiness that uses technology. In return, the service provider canreceive payment from the customer(s) under a subscription and/or feeagreement and/or the service provider can receive payment from the saleof advertising content to one or more third parties.

In still additional embodiments, the invention provides acomputer-implemented method, via a network. In this case, a computerinfrastructure, such as computer system/server 12 (FIG. 1), can beprovided and one or more systems for performing the processes of theinvention can be obtained (e.g., created, purchased, used, modified,etc.) and deployed to the computer infrastructure. To this extent, thedeployment of a system can comprise one or more of: (1) installingprogram code on a computing device, such as computer system/server 12(as shown in FIG. 1), from a computer-readable medium; (2) adding one ormore computing devices to the computer infrastructure; and (3)incorporating and/or modifying one or more existing systems of thecomputer infrastructure to enable the computer infrastructure to performthe processes of the invention.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A computer-implemented method comprising:storing, by a computing device, pixel-based classification rules in amemory of the computing device; storing, by the computing device, videouploading rules that identify a subset of a plurality of camerasimplemented within a vehicle for which video should be uploaded in thememory of the computing device; detecting, by the computing device,satisfaction of video upload event criteria based on video or image datafrom at least one of the plurality of cameras and vehicle informationcomprising one of vehicle sensor information and vehicle diagnosticinformation; determining, by the computing device, a subset of theplurality of cameras based on the detecting the satisfaction of thevideo upload event criteria; determining an event type based on thesatisfaction of the video upload event criteria; and uploading, by thecomputing device, video captured by only the subset of the plurality ofcameras to a video storage server; wherein the uploading comprises:determining, based on the event type, one of a plurality of differentvideo storage servers associated with different parties; and uploadingthe video captured by only the subset of the plurality of cameras to thedetermined one of the plurality of different video storage servers. 2.The method of claim 1, further comprising determining an event typebased on the satisfaction of the video upload event criteria, whereinthe subset of the plurality of cameras are further determined based onthe event type.
 3. The method of claim 2, wherein the event typeincludes at least one of: a road hazard; a vehicle accident; asurrounding vehicle accident; and aggressive driving.
 4. The method ofclaim 1, wherein the uploading the video includes uploading a snippet ofvideo for a time window.
 5. The method of claim 4, wherein the timewindow is determined based on satisfaction of the video upload eventcriteria.
 6. The method of claim 1, wherein: the uploading the videoincludes uploading metadata associated with the video, the metadataincluding: date and time of the video capture; the event type; vehicleowner information; registration information; license plate information;vehicle make and model; and vehicle location based on global positioningsystem (GPS) data received by vehicle diagnostic system; and theplurality of cameras implemented within the vehicle includes: afront-facing camera; a rear-facing camera; side-facing cameras; anddiagonal-facing cameras, all of which capture video while the vehicle isbeing driven.
 7. The method of claim 1, further comprising: detectingobjects, motions, or patterns based on the pixel-based classificationrules; receiving, by the computing device, manual instruction to uploadvideo captured by the plurality of cameras to a video storage server;creating, by the computing device, a new rule based on the receiving themanual instruction; automatically detecting, by the computing device,another event based on the new rule; and automatically uploading, by thecomputing device, video data based on the automatically detecting. 8.The method of claim 1, wherein the detecting the satisfaction of thevideo upload event criteria includes detecting that a value for the tirepressures or impact sensors satisfies a threshold.
 9. The method ofclaim 1, wherein a service provider at least one of creates, maintains,deploys and supports the computing device.
 10. The method of claim 1,wherein steps of claim 1, are provided by a service provider on asubscription, advertising, and/or fee basis.
 11. The method of claim 1,wherein the computing device includes software provided as a service ina cloud environment.
 12. The method of claim 1, further comprisingdeploying a system for triggering the uploading of video, comprisingproviding a computer infrastructure operable to perform the steps ofclaim
 1. 13. The method of claim 1, wherein the uploading additionallycomprises uploading the video captured by only the subset of theplurality of cameras to another video storage server associated with adriver of the vehicle.
 14. A computer program product comprising acomputer readable storage medium having program instructions embodiedtherewith, the program instructions executable by a computing device tocause the computing device to: store pixel-based classification rules ina memory of a computing device; store video uploading rules thatidentify a subset of a plurality of cameras implemented within a vehiclefor which video should be uploaded in the memory of the computingdevice; detect satisfaction of video upload event criteria based onvideo or image data from at least one of the plurality of cameras andvehicle information comprising one of vehicle sensor information andvehicle diagnostic information; determine a subset of the plurality ofcameras based on the detecting the satisfaction of the video uploadevent criteria; determine an event type based on the satisfaction of thevideo upload event criteria; and upload video captured by only thesubset of the plurality of cameras to a video storage server, whereinthe uploading comprises uploading, based on the event type, to one of aplurality of different video storage servers associated with differentparties; and the plurality of different video storage servers comprise:a first video storage server associated with a first party; and a secondvideo storage server associated with a second party different than thefirst party.
 15. The computer program product of claim 14, wherein theprogram instructions cause the computing device to: detect objects,motions, or patterns based on the pixel-based classification rules;receive manual instruction to upload video captured by the plurality ofcameras to a video storage server; create a new rule based on thereceiving the manual instruction; automatically detect another eventbased on the new rule; and automatically upload video data based on theautomatically detecting.
 16. The computer program product of claim 14,wherein the detecting the satisfaction of the video upload eventcriteria includes detecting that a value for the tire pressures orimpact sensors satisfies a threshold.
 17. A system comprising: a CPU, acomputer readable memory and a computer readable storage mediumassociated with a computing device; program instructions to storepixel-based classification rules in a memory of a computing device;program instructions to store video uploading rules that identify asubset of a plurality of cameras implemented within a vehicle for whichvideo should be uploaded in the memory of the computing device; programinstructions to detect satisfaction of video upload event criteria basedon video or image data from at least one of the plurality of cameras andvehicle information comprising one of vehicle sensor information andvehicle diagnostic information; program instructions to determine asubset of the plurality of cameras based on the detecting thesatisfaction of the video upload event criteria; program instructions todetermine an event type based on the satisfaction of the video uploadevent criteria; and program instructions to upload video captured byonly the subset of the plurality of cameras to a video storage server,wherein the uploading comprises: uploading to a first video storageserver associated with a first party when the event type is a firstevent type; and uploading to a second video storage server associatedwith a second party, different than the first party, when the event typeis a second event type different than the first event type; and theprogram instructions are stored on the computer readable storage mediumfor execution by the CPU via the computer readable memory.
 18. Thesystem of claim 17, further comprising program instructions to: detectobjects, motions, or patterns based on the pixel-based classificationrules; receive manual instruction to upload video captured by theplurality of cameras to a video storage server; create a new rule basedon the receiving the manual instruction; automatically detect anotherevent based on the new rule; and automatically upload video data basedon the automatically detecting.
 19. The system of claim 17, wherein thedetecting the satisfaction of the video upload event criteria includesdetecting that a value for the tire pressures or impact sensorssatisfies a threshold.
 20. The system of claim 17, wherein the uploadingadditionally comprises uploading the video captured by only the subsetof the plurality of cameras to another video storage server associatedwith a driver of the vehicle.